I think this article makes a valid point. However, if AI coding is considered gambling, then being a project manager overseeing multiple developers could also be seen as a form of gambling to a certain degree. In reality, there isn't much difference between the two. AI models are non-deterministic, and humans are also non-deterministic. You could assign the same task to two different developers and end up with entirely different results.

I think the addiction angle seems to make AI coding more similar to gambling. Some people seem to be disturbingly addicted to agentic coding. Much more so than traditional programming. To the point of doing destructive things like waking up in the middle of the night to check agents. Or giving an agent access to their bank account.

AI coding is gambling on slot machines, managing developers is betting on race horses.

You (in theory) have more control over the quality of the team you are managing, than the quality of the models you are using.

And the quality of code models puts out is, in general, well below the average output of a professional developer.

It is however much faster, which makes the gambling loop feel better. Buying and holding a stock for a few months doesn't feel the same as playing a slot machine.

I think this is a very good point. We have a natural bias toward human output as there is an illusion of full control - in reality even just from a solo dev perspective you've still got a load of hidden illogical persuasions that are influencing your code and how you approach a problem. AI has its own biases that come out of the nature its training on large unknowable data sets, but I'd argue the 'black box' thinking that comes out that isn't too different to the black box of the human mind. That's not at all to say that AI isn't worse (even if quicker) than top developer talent today writing handwritten code - just that the barrier to getting that level of quality isn't as insurmountable as it might appear.

It absolutely is. I did some consulting work for an environment where they have to churn out code to meet certain unchanging schedules, usually you can dumb down the process to make it more deterministic.

These guys had to manage very complex calculation engine based on we’ll just let it changes every year had to be correct had to be delivered by a certain date every year.

They had an army (100-200 people depending on various factors) of marginally skilled coding drones that were able to turn out the Java, COBOL or whatever it was predictably on that schedule without necessarily understanding any of the big picture or have any having any hope of so. Basically a software factory. There was about a dozen people who actually understood everything.

Only if you consider generative AI and human beings to be effectively equivalent.

Being a project manager is more or less something humans have been doing since the dawn of time.

Generative AI takes money as input and gives some output. If you don’t like the output, more money goes in. It’s far more akin to gambling than organizing human labor.

Framing anything with a common blanket concept usually fails to apply the same framing to related areas. A lot of things include some gambling, you need to compare how it was also 'gambling' before, and how 'not using AI' is also 'gambling', etc.

As @m00x points out "coding is gambling on slot machines, managing developers is betting on race horses."

I ssk an AI to play hangman with me and looked at it's reasoning. It didn't just pick a secret word and play a straightforward game of hangman. It continually adjusted the secret word based on the letters I guessed, providing me the "perfect" game of hangman. Not too many of my guesses were "right" and not too many "wrong" and I after a little struggle and almost losing, I won in the end.

It wasn't a real game of hangman, it was flat out manipulation, engagement farming. Do you think it's possible that AI does that in any other situations?

I don‘t think so. A project manager can give feedback, train their staff, etc. An AI coding model is all you get, and you have to wait until your provider trains a new model before you might see an improvement.

That says more about how you see developers than whether or not managers are in a sense gamblers.

This must be it. So many of our colleagues have been burnt by bad coworkers that they would rather burn everything down than spend another day working with them.

> AI models are non-deterministic, and humans are also non-deterministic. You could assign the same task to two different developers and end up with entirely different results.

Except, one can explain themselves (humans) and their actions can be held to account in the case of any legal issue whereas an AI cannot; making such an entity completely unsuitable for high risk situations.

This typical AI booster comparison has got to stop.

As a human, you generally have the opportunity make decent headway in understanding the other humans that you're working with and adjusting your instructions to better anticipate the outputs that they'll return to you. This is almost impossible with AI because of a combination of several factors:

>You are not an AI and do not know how an AI "thinks".

>Even if you come to be able to anticipate an AI's output, you will be undermined by the constant and uncontrollable update schedule imposed on you by AI platforms. Humans only make drastic changes like this under uncommon circumstances, like when they're going through large changes in their life, not as a matter of course.

>However, without this update schedule, problems that were once intractable will likely stay so forever. Humans, on the other hand, can grow without becoming completely unpredictable.

It's a Catch-22. AI is way closer to gambling.